Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ ...

Co-fonder and CTO, Paul Masters, described a novel way to arrange the elements of a chip to do both machine learning "training" -- where the neural network is developed -- as well as "inference ...

The photonic chip developed by MIT could change that by performing key computations at lightning speed, completing tasks in less than half a nanosecond. Deep neural networks process data through ...

However, there are some types of neural network computations that a photonic device cannot perform, requiring the use of off-chip electronics or other techniques that hamper speed and efficiency. Now, ...

The chip, which achieves 98% power efficiency ... especially in more intricate neural networks. The study, “An 8-channel high ...

One example could be Real-Time Neural Radiance Caching for Path Tracing. It's all pretty complicated, but the short version is that it uses AI to enable faster, lower-noise path tracing by handing ...

PIMIC, a US company that specialises in ultra-low-power AI semiconductor technology, has unveiled the Clarity NC100.

Researchers developed a technique that senses a model's electromagnetic 'signature' and compares it to other models run on ...

Through step-by-step prompts to ChatGPT4, starting with mimicking a single biological neuron and then linking more to form a network, they generated a full chip design that could be fabricated.

Syntiant’s advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient ...